| name | cognitive-rhythm-writing |
|---|---|
| description | 説明的な文章に緩急を設計するための規範。緩急を装飾ではなく認知モードの切替（観察→逡巡→断定→再観察）と未回収の緊張の管理として扱い、文の拍、段落の密度波形、節の入り方、緩みと駄文の判別、執筆後の機械的な点検手順を定める。読み物として読ませたい章・記事・解説文を生成するとき、または「密度はあるが平坦でおもしろくない」文章を診断・修正するときに使用する。 |
密度の高い文章が退屈になるのは、情報が多いからではなく、全文が同じ認知モードで書かれているからである。 この規範は、読者の認知モード（観察する、迷う、確信する、確かめ直す）を意図的に切り替え、常に「続きを読む理由」を維持することで、読み進める推進力を作る。
| # Me | |
| set from = "EMAIL@gmail.com" | |
| set realname = "NAME" | |
| # My credentials | |
| # For 2FA issue and application token from: | |
| # https://security.google.com/settings/security/apppasswords | |
| set smtp_url = "smtp://EMAIL@gmail.com@smtp.gmail.com:587/" | |
| set smtp_pass = "password" |
Authors: @h0j3n, @aniqfakhrul
Date: July 24, 2026
Certighost is an Active Directory Certificate Services (AD CS) vulnerability that allowed a low-privileged domain user to impersonate a Domain Controller and achieve domain compromise in the tested AD CS configuration. The issue was addressed in the July 2026 security updates.
The vulnerable path is an AD CS enrollment fallback known as a chase during directory-object resolution. By supplying request attributes such as cdc, an attacker could cause the Certification Authority (CA) to ask an attacker-controlled host for identity data belonging to a Domain Controller. The CA then used that data while issuing a certificate.
Complete guide for configuring Synaptics fingerprint readers (including Metallica MIS Touch) on Linux distributions using python-validity and fprintd.
This guide specifically covers Synaptics fingerprint sensors that require proprietary drivers:
| import UIKit | |
| final class MenuControl: UIControl { | |
| private let label: UILabel = { | |
| let label = UILabel() | |
| label.text = "Public API-Only Menu" | |
| label.font = .boldSystemFont(ofSize: 15) | |
| label.textAlignment = .center | |
| label.textColor = .white |
| #!/bin/bash | |
| # Script for QuadtreeAmogufier | |
| # https://github.com/snailcon/QuadtreeAmogufier | |
| cd "$(dirname $0)" | |
| if [[ $1 == clean ]]; then | |
| rm -f audio.ogg in/*.png out/*.png | |
| exit |
This is a field guide for the failure mode where Honcho is technically running, but the memory it produces is noisy, empty, or actively unhelpful.
The short version: Honcho is very sensitive to input quality. Garbage in, garbage out. If you feed the deriver recalled memory, assistant task history, tool chatter, temporary troubleshooting state, and every random user request as if it were durable autobiographical truth, Honcho will faithfully preserve garbage and then recall it later as context. That makes the agent feel haunted by its own transcript.
This document describes the symptoms we saw and the final changes that made Honcho useful in practice.
Quantitative type theory (QTT) is an extension of dependent type theory which allows us to track the number of computational (non-erased) uses of variables in well-typed lambda terms. With such usage information, QTT allows us to combine dependent types with substructural types, such as linear, affine or relevant types.
While in a Martin-Löf style type theory typing judgments are of form
x1 : A1, ..., xn : An ⊢ b : B, in QTT the bindings in the context
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
No, seriously, don't. You're probably reading this because you've asked what VPN service to use, and this is the answer.
Note: The content in this post does not apply to using VPN for their intended purpose; that is, as a virtual private (internal) network. It only applies to using it as a glorified proxy, which is what every third-party "VPN provider" does.
